Berechnung der Lärmemission von turbulenten Flammen mittels kompressibler Grobstruktursimulation und Direkter Numerischer Simulation

联合提案的首要目标是借助数值工具分析湍流燃烧噪声辐射的产生机理和定量预测。在与项目第一阶段的合作伙伴(TP1(Paschereit)、TP2(Janicka)、TP3(Schröder))的合作下，将试行通用燃烧器配置，以便燃烧器能够在稀薄预混合装置中运行。这一子项目的一个主要任务是利用直接数值模拟(DNS)方法，包括化学发光物质，加深对湍流预混火焰噪声产生机理的理解。借助该系统，可以评估噪声产生源之间的相关性，例如，非定常热释放和湍流波动的相互作用。将进一步开发在第一个资助期开发的基于OpenFOAM的域名系统解算器，并将创建一个火焰数据库，其中包含高分辨率的域名系统数据，作为验证/改进大涡模拟(LES)的参考。通过使用域名系统数据库，另一个目标仍然是调查和量化激发的化学发光物种(例如，OH*或CH*)与热释放速率的内在相关性。最后将使用高分辨率的可压缩大涡模拟，以便为TP3(Schröder)中的CAA解决方案提供输入值，并将来自DNS数据的分析结果与TP2(Janicka)一起实施到大涡模拟方法(可压缩和低mA)中。

The overriding objective of the joint proposal is to analyze the generation mechanism as well as the quantitative prediction of noise radiations from turbulent combustion with help of numerical tools. In co-operation with the partners of the first project phase (TP1 (Paschereit), TP2 (Janicka), TP3 (Schröder)) the generic burner configuration will be piloted such that the burner can be operated in the lean premixed re-gime. One major task of this subproject is to a gain deeper understanding of the noise generation mecha-nisms from turbulent premixed flames by using the direct numerical simulation (DNS) method, including chemiluminescent species. With help of the DNS it is possible to assess correlations between the noise gen-eration sources, e.g., the interaction of unsteady heat release and turbulent fluctuations. The OpenFOAM based DNS solver developed in the first funding period will be further developed and a flame data-base with highly resolved DNS data as reference for validating/improving large eddy simulations (LES) will be created. By use of the DNS data base, another objective remains to investigate and quantify the inherent correlation of excited chemiluminescent species (e.g. OH* or CH*) with the heat release rate. Highly-resolved compress-ible LES simulations will be used at the end in order to provide input values for the CAA solution in TP3 (Schröder) and to implement the achieved results from analysis of DNS data into the LES modeling methods (compressible and low-Ma) together with TP2 (Janicka).